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Imagine Alice has trained a machine learning model. Bob wants to verify that whether Alice actually trained the model or not, but Alice does not want to reveal her model (because the model is personal and she wants to keep it private). So Alice wants to prove to Bob that she has the model, while not revealing any information to Bob.

Is there any zero knowledge proof to be able to do this scenario?

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I am almost two years late to this, but I think this is what you are looking for: https://dl.acm.org/doi/10.1145/3411501.3418608 (Zero-Knowledge Proofs for Machine Learning)

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    $\begingroup$ Welcome to Cryptography We consider this as link only answer. You better provide some details of the paper... $\endgroup$
    – kelalaka
    May 8 at 18:35
  • $\begingroup$ I am confident the claims in the abstract are mostly false. We can not provide proof of accuracy on a well known public dataset because it is trivial to build a model with knowledge of the test set and build a model with arbitrary accuracy and zero value. proving it has accuracy is meaningless $\endgroup$
    – Meir Maor
    Jun 8 at 5:06

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